This repository contains MATLAB-code (and accompanying C-written routines) for plmDCA. plmDCA takes as input a Multiple Sequence Alignment and returns scores for pairwise (direct) interactions among the columns. The method is described at length in:
(1) M. Ekeberg, C. Lövkvist, Y. Lan, M. Weigt, E. Aurell, Improved contact prediction in proteins: Using pseudolikelihoods to infer Potts models, Phys. Rev. E 87, 012707 (2013)
(2) M. Ekeberg, T. Hartonen, E. Aurell, Fast pseudolikelihood maximization for direct-coupling analysis of protein structure from many homologous amino-acid sequences, J. Comput. Phys. 276, 341-356 (2014)
If you use plmDCA (modified or as is) for your own research, cite the papers above. See the files for copyright conditions and instructions on how to use the code. Send comments and suggestions to magnus.ekerberg (at) gmail (dot) com .
There are two versions of plmDCA: the original "symmetric" version from (1), and the new "asymmetric" from (2). The latter is faster, while producing almost identical output as the original. At present, we therefore recommend the asymmetric variant.
Keywords: plmDCA, pseudolikelihood, direct-coupling analysis, protein structure prediction, contact map, multiple sequence alignment, inverse Ising, Potts model, pairwise Markov random field, learning, inference